IoT devices have some special characteristics, such as mobility, limited performance, and distributed deployment, which makes it difficult for traditional centralized access control methods to support access control in current large-scale IoT environment. To address these challenges, this paper proposes an access control system in IoT named fabric-iot, which is based on Hyperledger Fabric blockchain framework and attributed based access control (ABAC). The system contains three kinds of smart contracts, which are Device Contract (DC), Policy Contract (PC), and Access Contract (AC). DC provides a method to store the URL of resource data produced by devices, and a method to query it. PC provides functions to manage ABAC policies for admin users. AC is the core program to implement an access control method for normal users. Combined with ABAC and blockchain technology, fabric-iot can provide decentralized, fine-grained and dynamic access control management in IoT. To verify the performance of this system, two groups of simulation experiments are designed. The results show that fabric-iot can maintain high throughput in largescale request environment and reach consensus efficiently in a distributed system to ensure data consistency.

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Due to the high-energy efficiency and scalability, the clustering routing algorithm has been widely used in wireless sensor networks (WSNs). In order to gather information more efficiently, each sensor node transmits data to its Cluster Head (CH) to which it belongs, by multi-hop communication. However, the multi-hop communication in the cluster brings the problem of excessive energy consumption of the relay nodes which are closer to the CH. These nodes’ energy will be consumed more quickly than the farther nodes, which brings the negative influence on load balance for the whole networks. Therefore, we propose an energy-efficient distributed clustering algorithm based on fuzzy approach with non-uniform distribution (EEDCF). During CHs’ election, we take nodes’ energies, nodes’ degree and neighbor nodes’ residual energies into consideration as the input parameters. In addition, we take advantage of Takagi, Sugeno and Kang (TSK) fuzzy model instead of traditional method as our inference system to guarantee the quantitative analysis more reasonable. In our scheme, each sensor node calculates the probability of being as CH with the help of fuzzy inference system in a distributed way. The experimental results indicate EEDCF algorithm is better than some current representative methods in aspects of data transmission, energy consumption and lifetime of networks.

Accurate and complete educational records are a valuable asset for people. In recent years, educational records have been digitized. However, there are still two key challenges that have not been resolved. One is to achieve secure and privacy-preserving storage of educational records, while another concern how to realize the sharing of educational records and ensure the security of the sharing process. In this paper, we propose EduRSS, a blockchain-based storage and sharing scheme for educational records is proposed, which combines blockchain, storage servers, and cryptography techniques to create a reliable and safe environment. In our proposal, the blockchain technology is used to ensure the security and reliability of data storage, while the smart contracts on the blockchain are used to regulate the process of storage and sharing. More precisely, the off-chain storage servers store the original educational records in encrypted form, while the hash information of the records is stored on the blockchain. The off-chain records are anchored periodically with the hash information on the blockchain to ensure the security of data storage. Cryptography techniques are utilized to handle records encryption and messages digital signature. To assess the effectiveness of EduRSS, we designed and tested a proof of concept of this scheme. The relative security analysis shows that EduRSS is safe and has a lower computational cost than that of the CP-ABE and the MA-CPABE schemes.INDEX TERMS Educational records, blockchain, smart contract, secure storage and sharing.HONGZHI LI received the M.S. degree in computer science and engineering from the Wuhan University of Technology. He is currently pursuing the Ph.D. degree with Shanghai Maritime University. His current research interests include blockchain technology and information security.

SUMMARYIn this paper, we revisit a generally accepted opinion: implementing Elliptic Curve Cryptosystem (ECC) over GF(2m) on sensor motes using smallt appropriate because XOR multiplication over GF(2m) is not efficiently supported by current low-powered microprocessors. Although there are some implementations over GF(2m) on sensor motes, their performances are not satisfactory enough to be used for wireless sensor networks (WSNs). We have found that a field multiplication over GF(2m) are involved in, a number of redundant memory accesses and its inefficiency is originated from this problem. Moreover, the field reduction process also requires many redundant memory accesses. Therefore, we propose some techniques for reducing unnecessary memory accesses. With the proposed strategies, the running time of field multiplication and reduction over GF(2163) can be decreased by 21.1% and 24.7%, respectively. These savings noticeably decrease execution times spent in Elliptic Curve Digital Signature Algorithm (ECDSA) operations (signing and verification) by around 15-19%. We present TinyECCK (Tiny Elliptic Curve Cryptosystem with Koblitz curve -a kind of TinyOS package supporting elliptic curve operations) which is the first implementation of Koblitz curve on sensor motes as far as we know. Through comparisons with existing software implementations of ECC built in C or hybrid of C and inline assembly on sensor motes, we show that TinyECCK outperforms them in terms of running time, code size and supporting services. Furthermore, we show that a field multiplication over GF(2m) can be faster than that over GF(p) on 8-bit Atmega128 processor by comparing TinyECCK with TinyECC, a well-known ECC implementation over GF(p). TinyECCK with sect163kl can generate a signature and verify it in 1.37 and 2.32 secs on a Micaz mote with 13,748-byte of ROM and 1,004-byte of RAM.

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